System and method for forest management using stand development performance as measured by LAI

ABSTRACT

A system and method for identifying stands or portions thereof that are not growing as expected. In one embodiment, a computer system compares a measured leaf area index of a stand that is determined from remotely sensed data to an expected leaf area index. The computer system identifies stands or portions of stands where the measured leaf area index is greater than the expected leaf area index and/or stands or portions of stands where the measured leaf area index is less than the expected leaf area index. In one embodiment, the comparison is used to identify stands or portions thereof where silviculture treatments may be necessary.

TECHNICAL FIELD

The technology disclosed herein relates to computer systems for use inforest management and in particular to systems for identifying stands orportions thereof that are not growing as expected and/or forrecommending stands for silviculture treatments.

BACKGROUND

In the commercial growing and harvesting of forest products, trees arenot simply planted and harvested at a pre-determined time in the future.Instead, many silviculture techniques may be applied to a forest standduring its growth cycle in order to achieve an optimal yield for aparticular type of forest product. Such techniques can include selectivethinning of desired trees, the removal of competing trees, brush orother vegetation, the application of fertilizer, etc.

One difficulty encountered in active management forestry is to knowwhich stands are not growing as expected and therefore may needfertilization, thinning or the administration of other silviculturaltechniques. The conventional method of forest management is to sendforesters into a stand to physically survey the stand and recommend theapplication of one or more silviculture techniques if needed. While suchan approach can work for relatively small forests, it can be costprohibitive to physically inspect all the areas of large commercialforests that may extend over a wide large geographical area. Inaddition, even if physical inspection is possible, a survey crewgenerally doesn't know ahead of time what the condition of the standwill be prior to its inspection. Therefore, the crew often has to returnto the site with the proper equipment in order to perform a recommendedsilviculture technique.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a computer system for assessing how stand is growingand/or for identifying stands that may need the application of one ormore silviculture techniques in accordance with an embodiment of thedisclosed technology;

FIG. 2 illustrates a representative plot of a leaf area index versus theage of a stand for a number of different forest stands;

FIG. 3 illustrates a map produced in accordance with an embodiment ofthe disclosed technology that identifies the location of over and/orunderperforming tree stands or portions thereof in accordance with anembodiment of the disclosed technology; and

FIG. 4 is a flowchart of steps performed in accordance with oneembodiment of the disclosed technology to identify over and/orunderperforming tree stands and/or for recommending silviculturetreatments for the stands.

DETAILED DESCRIPTION

As indicated above, one challenge faced by foresters and forest productcompanies is being able to determine how a stand of trees is growing ina cost effective manner. If it is known that a stand is not growing asexpected, a forester can recommend that one or more silviculturetreatments be applied to the stand in order to improve its growthperformance. While foresters could determine stand conditions if thestand is physically inspected, it is often cost prohibitive, subjectivein nature due to how different foresters interpret the condition of astand, and sometimes physically impossible to physically inspect everyacre of each stand in a forest. In addition, even if a stand isphysically inspected and a forester makes recommendations for particularsilviculture techniques to be applied, the forester may not have theappropriate tools or equipment readily at hand in order to apply therecommended technique. Therefore, the forester has to return with theappropriate equipment to apply the recommended technique, thusincreasing the overall cost and time required for forest management.

To address these problems and others, the disclosed technology is acomputer system that operates to estimate how tree stands or portionsthereof are growing in a forest. In one embodiment, the computer systemidentifies stands that are not growing as expected so that a forestercan recommend the application of one or more silviculture treatments tothe stand.

In one embodiment, a computer system uses remotely sensed data todetermine whether a forest stand is growing as expected. Stands that aregrowing at a rate that is greater than expected are classified as overperforming stands while those that are growing at a rate that is lessthan expected are classified as under performing stands.

While it may seem counterintuitive that over performing stands may needthe application of a silviculture treatment, such stands typicallycontain undesired trees or other vegetation that can be detected byremote sensing equipment and that are competing with a desired treespecies in the stand. Therefore, the treatment applied to such standsusually involves the removal of the undesired trees or competingvegetation by thinning, applying herbicides or other vegetation controlmethods. On the other hand, under performing stands may indicatemortality problems due to insects, diseases, fire, or competition withundesired vegetation that could be undetected by remote sensingequipment (e.g. deciduous species will not be detected by remote sensingdata if collected in winter time). Treatments applied to underperformingstands may include the removal of undesired vegetation and/or theapplication of fertilizers to the stand.

In accordance with one embodiment of the disclosed technology, how wella stand is growing in a forest is determined by comparing the currentleaf area index of the stand to an expected leaf area index. In oneembodiment, the leaf area index is measured from remotely sensed data.FIG. 1 illustrates a system for estimating how well a stand is growingfrom remotely sensed data. As shown, a forest stand 10 is planted with adesired species of trees 20. In addition, the stand may include one ormore unwanted species of trees 30 that can become established by, forexample, natural seeding. The undesirable species of trees 30 maycompete for light, nutrients and water with the desired species of tree20 to be grown in the stand. In addition, the stand 10 may includevegetation 40 such as shrubs and the like that also compete with thedesired species 20 for water and nutrients, etc.

To estimate how well the desired species 20 in the stand is growing, theleaf area index (LAI) for the stand 10 is measured. In one embodiment,remotely sensed data are obtained from satellite images such as the typeavailable from the Landsat imaging system 60. The satellite imagingsystem is used to capture an image of the geographic region thatincludes the stand 10. The leaf area index of a stand can be calculatedfrom the satellite images of the stand as will be explained below.

As will be appreciated by those skilled in the art, satellite imagesoften contain image data that is obtained in multiple spectral bands. Inone embedment, the leaf area index of a stand is calculated from thevegetation indexes (VI) of a stand. As will be appreciated by thoseskilled in the art of remote sensing and forestry, the VI for a stand isbased on ratios of the reflectance detected in the red and near infraredspectral bands. The techniques and equations for calculating the leafarea index from the corresponding VI in an area of a satellite image arewell-known to those of ordinary skill in the art.

In another embodiment, the leaf area index of a stand is measured fromother types of remotely sensed data such as Light Detection and Ranging(LiDAR). As will be appreciated by those skilled in the art, LiDAR datarepresents the detection of a laser pulse that is carried over a forestor other area of interest by an aircraft, such as a helicopter or afixed wing airplane 70. A LiDAR system carried over the area of interestdirects a pulsed laser beam towards the ground. Laser pulses that arereflected back to the LiDAR system are detected. Because the altitudeand location of the aircraft are known, each detected pulse can beassigned a three dimensional position to create a topographical map ofthe ground over which the aircraft is flown.

In one embodiment, the leaf area index for a forest stand is calculatedfrom LiDAR data points having a height that falls within an expectedcanopy height of the forest. In one embodiment, LiDAR data points aredetected that have a height above ground that is within an expectedcanopy height that is statistically determined or modeled for the treespecies in the stand, the age of trees, the geographic area of thestand, soil conditions and other factors. The leaf area index for astand or portion thereof is determined by comparing the number ofreflected LiDAR data points in this height range to the total number ofLiDAR data points detected. However, other techniques for determiningthe leaf area index such as aerial multi-spectral imagery orhyperspectral imagery could also be used. Furthermore, hand held devicesfor measuring the leaf area index could be used.

Once the leaf area index of the stand 10 is measured from the remotelysensed data, it is compared to an expected leaf area index. If themeasured leaf area index of a stand is higher than expected, the standis classified as over performing. In such a stand, it is likely thatunwanted species 30 and/or vegetation 40 are growing in the stand andcompeting with the desired species of trees 20. Therefore, such a standmay be identified as needing selective thinning and/or the applicationof herbicides of other silviculture treatments to control competition.Alternatively, if the measured leaf area index of the stand 10 orportion thereof is less than an expected leaf area index, such a standis identified as under performing and may be also be marked for theapplication of hardwood competing vegetation release, fertilizer, orother treatments to increase the growth of desired trees in the stand.

In accordance with one embodiment of the disclosed technology, acomputer system 100 executes a sequence of program instructions storedon a non-transitory computer readable media 120 such as a CD ROM, harddrive, DVD, flash drive etc. Alternatively, the program instructions canbe received from a remote computer over a computer communication linksuch as the Internet. Processor electronics within the computer system100 execute the program instructions to estimate how well each stand orportion of a stand is growing. In one embodiment, the computer system100 operates to receive remotely sensed data for an area of interestthat includes the stand in question from a database 140. From theremotely sensed data, the leaf area index for a stand is measured. Inone embodiment, the remotely sensed data comes from satellite images ofthe area of interest. In another embodiment, the remotely sensed data isLiDAR data. The measured leaf area index for the stand in question iscompared against an expected leaf area index for the stand.

The computer system 100 identifies stands that have a measured leaf areaindex that is greater than or less than the expected leaf area indexdetermined for the stand and stored in a database 150. In oneembodiment, the computer system produces a map 160 that identifiesstands or portions of stands where the measured leaf area index isgreater than, equal to or less than the expected leaf area index for thestand. The map 160 can be in electronic form for viewing on a computermonitor or the like. Alternatively, the map 160 can be printed on paperor other media. The map 160 identifies geographic locations whereforesters may consider the application of silviculture techniques inaccordance with how the measured leaf area index for the stand compareswith the expected leaf area index for the stand. Alternatively, thecomputer system 100 can produce a list 170 that identifies stands orportions of stands where treatments are recommended. The list mayspecify the type of treatment to be applied to the stand. Alternatively,the list 170 may identify stands or portions of stands that are eitherover or under performing and a forester or other individual candetermine what treatments are needed.

FIG. 2 illustrates a plot 200 of a number of points each representingthe measured leaf area index of a stand versus the age of the trees inthe stand. The leaf area index measured for each point in the plot 200may be determined via any number of techniques such as by measuring theleaf area index from remotely sensed data such as satellite images orLiDAR data. Alternatively, the leaf area index of a stand may bemeasured from a physical inspection of the stand using light measurementtools such as the LAI-2000 available from LiCOR BioSciences or theAccupar LP-80 available from Decagon Devices Inc., or from amathematical growth model. Although the graph illustrated in FIG. 2shows the measured leaf area index values for stands up to 12 years inage, it will be appreciated that measurements can be taken for stands ofany age up to harvest.

Once enough data points have been determined for a particular speciesrepresented by the plot 200, the average expected leaf area index 210can be determined and graphed versus the age of the stand. Additionalstatistical techniques can be used to determine an upper normal range220 and a lower normal range 230. The area between the lower normalrange 230 and the upper normal range 220 defines the expected leaf areaindex of the tree species versus age. Once the expected leaf area indexis measured for a stand or portion of a stand in question, the measuredleaf area index for the stand in question is compared to the expectedleaf area index.

In the plot shown in FIG. 2, a region 260 identifies LAI/stand agevalues where the leaf area index is greater than the expected leaf areaindex. Similarly, a region 270 identifies LAI/stand age values where theleaf area index is below the expected leaf area index.

In another embodiment, the expected leaf area index of a stand can bedetermined from a growth model that is specific to the species inquestion. The growth model can take into account such factors as thegeographic location of a stand, the soil conditions of the stand,silviculture techniques applied to the stand (e.g., thinning,fertilizer, etc.), weather conditions and other factors. The growthmodel is typically empirical in nature and is determined from many yearsof ground truth measurements and other collected data. The expectedgrowth values from the model can then be converted to expected values ofleaf area index by utilizing the growth efficiency (GE), normallydefined as the growth per unit of leaf area.

FIG. 3 illustrates a chart or map 300 produced by the computer systemthat indicates the boundaries of individual stands in a forest region.The chart 300 shows how the leaf area index measured for small portionsof a stand (i.e., pixels in the chart) compares with an expected leafarea index. In one embodiment, each pixel in the chart 300 represents anarea of approximately 100 feet by 100 feet. However, it will beappreciated that other pixel areas could be used depending on theresolution of the remote sensing equipment used to determine the leafarea index

By measuring and comparing the leaf area index for regions that aresmaller than the entire stand, it can easily be seen if an entire standmay need silviculture treatments or just a portion of the stand. Eachpixel in the chart 300 can be color-coded or otherwise differentiateddepending upon the comparison of the measured leaf area index and theexpected leaf area index. The chart 300 may be shown on a computerdisplay or printed. In another embodiment, those stands or portions ofstands that have measured leaf area indices that are above or below theexpected leaf area index can be included in a report. The stands orportions of the stands can be identified by number or by geographiccoordinates so that foresters can determine what, if any, treatmentsneed to be applied.

In yet another embodiment, the computer system makes a recommendation ofwhat treatment should be applied to a stand or portion thereof based onthe comparison of the measured leaf area index with the expected leafarea index.

FIG. 4 illustrates a flowchart of steps performed by a computer systemin accordance with one embodiment of the disclosed technology toestimate how well a stand is growing by comparing the measured leaf areaindex of the stand as determined from remotely sensed data with anexpected leaf area index.

Beginning at 400, a computer system receives remotely sensed data, suchas Landsat image data or LiDAR data for a stand or portion thereof. At404, the computer system converts the remotely sensed data to a measuredleaf area index for the stand. At 406, the computer system compares themeasured leaf area index for the stand to an expected leaf area index.

At 408, it is determined if the measured leaf area index of the stand isgreater than the expected leaf area index. If so, the stand is markedfor thinning or other silviculture techniques at 410. Such techniquesgenerally serve to remove or decrease vegetation that is competing withthe desired species in the stand.

If the answer at 408 is no, the computer determines at 412 if themeasured leaf area index of the stand is less than the expected leafarea index. If so, the current leaf area index is compared to one ormore leaf area index values from previous years at 414. If the standleaf area index shows continued declining values, the stand is marked at416 as potentially being damaged such as from insects, disease or fromnatural causes, e.g., storms, etc. If the stand leaf area index shows aslow increase of leaf area index from a previously measured leaf areaindex, the stand is marked at 418 for hardwood release, fertilization orother silviculture techniques that may increase the growth rate ofdesired species in the stand.

At 420, the computer system generates a map or list that identifiesthose stands or portions thereof where the measured leaf area index isgreater than or less than (i.e., differs from) the expected leaf areaindex. In addition, or alternatively, the computer system can producereports with lists showing stands or portions thereof where the measuredleaf area index differs from the expected leaf area index. The reportmay also suggest a particular silviculture treatment to be applied.

By viewing the map or the reports of where the measured leaf area indexdiffers from an expected leaf area index, a forester or other individualcan prescribe the application of one or more silviculture treatments.Alternatively, the location of such stands or portions thereof can beput on a list to physically inspect before making such a recommendation.In addition, because the map or list shows if a stand is over or underperforming, the forester can be prepared to treat the stand so that thecorrect tools are brought along when expecting a stand, thereby reducingthe chance that multiple trips are necessary to treat the stand.

Although the disclosed technology is described in terms of growingtrees, it will be appreciated that the technology can be used for othercrops as well. For example, the technology can be used for determiningif other crops such as bamboo, rice, corn, wheat or other vegetation aregrowing as expected. Therefore, the term “stand” is meant to includemore than just a stand of trees.

Embodiments of the subject matter and the operations described in thisspecification can be implemented in digital electronic circuitry, incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Embodiments of the subject matterdescribed in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on a non-transitory computer readable medium forexecution by, or to control the operation of, data processing apparatus.

The non-transitory computer readable medium can be, or can be includedin, a computer-readable storage device, a computer-readable storagesubstrate, a random or serial access memory array or device, or acombination of one or more of them. Moreover, while a computer storagemedium is not a propagated signal, a computer storage medium can be asource or destination of computer program instructions encoded in anartificially-generated propagated signal. The computer storage mediumalso can be, or can be included in, one or more separate physicalcomponents or media (e.g., multiple CDs, disks, or other storagedevices). The operations described in this specification can beimplemented as operations performed by a data processing apparatus ondata stored on one or more computer-readable storage devices or receivedfrom other sources.

The term “data processing apparatus” encompasses all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing. The apparatus can includespecial purpose logic circuitry, e.g., an FPGA (field programmable gatearray) or an ASIC (application-specific integrated circuit). Theapparatus also can include, in addition to hardware, code that createsan execution environment for the computer program in question, e.g.,code that constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.The apparatus and execution environment can realize various differentcomputing model infrastructures, such as web services, distributedcomputing and grid computing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored in a portion of a file that holds other programsor data (e.g., one or more scripts stored in a markup languagedocument), in a single file dedicated to the program in question, or inmultiple coordinated files (e.g., files that store one or more modules,sub-programs, or portions of code). A computer program can be deployedto be executed on one computer or on multiple computers that are locatedat one site or distributed across multiple sites and interconnected by acommunication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory, arandom access memory or both. The essential elements of a computer are aprocessor for performing actions in accordance with instructions and oneor more memory devices for storing instructions and data. Generally, acomputer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto-optical disks, or optical disks.However, a computer need not have such devices. Moreover, a computer canbe embedded in another device, e.g., a mobile telephone, a personaldigital assistant (PDA), a mobile audio or video player, a game console,a Global Positioning System (GPS) receiver, or a portable storage device(e.g., a universal serial bus (USB) flash drive), to name just a few.Devices suitable for storing computer program instructions and datainclude all forms of non-volatile memory, media and memory devices,including by way of example semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic disks, e.g., internal harddisks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., an LCD (liquid crystal display), LED(light emitting diode), or OLED (organic light emitting diode) monitor,for displaying information to the user, a keyboard and a pointingdevice, e.g., a mouse or a trackball, by which the user can provideinput to the computer. In some implementations, a touch screen can beused to display information and to receive input from a user. Otherkinds of devices can be used to provide for interaction with a user aswell; for example, feedback provided to the user can be any form ofsensory feedback, e.g., visual feedback, auditory feedback, or tactilefeedback; and input from the user can be received in any form, includingacoustic, speech, or tactile input. In addition, a computer can interactwith a user by sending documents to and receiving documents from adevice that is used by the user; for example, by sending web pages to aweb browser on a user's client device in response to requests receivedfrom the web browser.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back-end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front-end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back-end, middleware, or front-end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

The computing system can include any number of clients and servers. Aclient and server are generally remote from each other and typicallyinteract through a communication network. The relationship of client andserver arises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

From the foregoing, it will be appreciated that specific embodiments ofthe invention have been described herein for purposes of illustration,but that various modifications may be made without deviating from thescope of the invention. Accordingly, the invention is not limited exceptas by the appended claims.

I claim:
 1. A computer system comprising: a memory for storing asequence of program instructions; processor electronics configured toexecute the program instructions to identify stands of vegetation thatare not growing as expected by: measuring a leaf area index for a standof vegetation or portion thereof of a certain age; comparing themeasured leaf area index to an expected leaf area index determined foran age of vegetation corresponding to the age of the vegetation in thestand; and identifying stands or portions thereof as over performing orunderperforming where the measured leaf area index differs from theexpected leaf area index.
 2. The computer system of claim 1, wherein theprocessor electronics are configured to execute program instructions toproduce a map that indicates one or more stands or portions thereofwhere the measured leaf area index is above the expected leaf areaindex.
 3. The computer system of claim 1, wherein the processorelectronics are configured to execute program instructions to produce amap that indicates one or more stands or portions thereof where themeasured leaf area index is below the expected leaf area index.
 4. Thecomputer system of claim 1, wherein the processor electronics areconfigured to execute program instructions to measure the leaf areaindex of a stand from LiDAR data.
 5. The computer system of claim 1,wherein the processor electronics are configured to execute programinstructions to measure the leaf area index of a stand from satelliteimage data.
 6. The computer system of claim 1, wherein the processorelectronics are configured to execute program instructions to measurethe leaf area index of a stand from aerial multispectral data.
 7. Thecomputer system of claim 1, wherein the processor electronics areconfigured to execute program instructions to measure the leaf areaindex of a stand from aerial hyperspectral data.
 8. The computer systemof claim 1, wherein the processor electronics are configured to producea report listing one or more silviculture treatments to be applied to astand based on the comparison of the measured leaf area index and theexpected leaf area index.
 9. A non-transitory computer readable mediawith instructions thereon that are executable by processor electronicsto identify stands that are not growing as expected by: measuring a leafarea index for a stand of vegetation or portion thereof of a certainage; comparing the measured leaf area index to an expected leaf areaindex determined for an age of vegetation corresponding to the age ofthe vegetation in the stand; and identifying stands or portions thereofas over performing or underperforming where the measured leaf area indexdiffers from the expected leaf area index.
 10. The non-transitorycomputer readable media of claim 9, further comprising: instructionsexecutable by the processor electronics to produce a map that indicatesone or more stands or portions thereof where the determined leaf areaindex is above the expected leaf area index.
 11. The non-transitorycomputer readable media of claim 9, further comprising: instructionsexecutable by the processor electronics to produce a map that indicatesone or more stands or portions thereof where the measured leaf areaindex is below the expected leaf area index.
 12. The non-transitorycomputer readable media of claim 9, further comprising: instructionsexecutable by the processor electronics to measure the leaf area indexof a stand from LiDAR data.
 13. The non-transitory computer readablemedia of claim 9, further comprising: instructions executable by theprocessor electronics to determine a leaf area index of a stand fromsatellite image data.
 14. The non-transitory computer readable media ofclaim 9, further comprising: instructions executable by the processorelectronics to measure a leaf area index of a stand from aerialmultispectral data.
 15. The non-transitory computer readable media ofclaim 9, further comprising: instructions executable by the processorelectronics to measure a leaf area index of a stand from aerialhyperspectral data.
 16. The non-transitory computer readable media ofclaim 9, further comprising: instructions executable by the processorelectronics produce a report, listing one or more silviculturetreatments to be applied to a stand based on the comparison of themeasured leaf area index and the expected leaf area index.